Agent skill

agentic-layer-audit

Audit codebase for agentic layer coverage and identify gaps. Use when assessing agentic layer maturity, identifying investment opportunities, or evaluating primitive coverage.

Stars 163
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/agentic-layer-audit

SKILL.md

Agentic Layer Audit Skill

Evaluate a codebase's agentic layer maturity and identify investment opportunities.

When to Use

  • Assessing current agentic layer coverage
  • Identifying gaps in automation
  • Planning agentic layer investments
  • Measuring progress toward 50%+ agentic time

Core Concept

"Am I working on the agentic layer or am I working on the application layer?"

This skill helps answer that question by auditing what exists.

Audit Checklist

1. Commands Directory

Check for .claude/commands/ or equivalent:

markdown
Look for:
- chore.md      # Chore planning template
- bug.md        # Bug fix template
- feature.md    # Feature planning template
- implement.md  # Implementation HOP
- test.md       # Test execution template
- review.md     # Review template

2. Specs Directory

Check for specs/ or equivalent:

markdown
Look for:
- Issue-based specs (issue-*.md)
- Generated plans (chore-*.md, feature-*.md)
- Deep specs (complex multi-file architectures)

3. ADW Directory

Check for adws/ or equivalent:

markdown
Look for:
- adw_modules/agent.py  # Core agent execution
- Gateway scripts (adw_prompt.py, adw_slash_command.py)
- Composed workflows (adw_*_*.py)
- Triggers (trigger_*.py)

4. Hooks Directory

Check for .claude/hooks/ or equivalent:

markdown
Look for:
- pre_tool_use hooks
- post_tool_use hooks
- user_prompt_submit hooks

5. Agent Output Directory

Check for agents/ or equivalent:

markdown
Look for:
- ADW ID directories
- State files (adw_state.json)
- Output files (cc_*.jsonl, cc_*.json)

6. Worktree Support

Check for trees/ or equivalent:

markdown
Look for:
- Git worktree setup
- Isolation configuration
- Port allocation patterns

Coverage Scoring

Component Points Present?
.claude/commands/ 20
specs/ 15
adws/ 25
adw_modules/agent.py 20
hooks/ 10
agents/ 5
trees/ 5

Total: 100 points

Score Level Recommendation
0-20 None Start with minimum viable layer
21-40 Basic Add composed workflows
41-60 Developing Add hooks and triggers
61-80 Advanced Add worktree isolation
81-100 Complete Focus on optimization

Key Memory References

  • @agentic-layer-structure.md - What to look for
  • @the-guiding-question.md - Why this matters
  • @agentic-vs-application.md - Layer separation

Output Format

markdown
## Agentic Layer Audit Report

**Project:** {name}
**Audit Date:** {date}
**Coverage Score:** {score}/100

### Components Found
- [x] .claude/commands/ (5 templates)
- [x] specs/ (12 specs)
- [ ] adws/ (not found)
- [ ] hooks/ (not found)

### Maturity Level
{Level} - {Recommendation}

### Gaps Identified
1. No ADW scripts for workflow orchestration
2. No hooks for event-driven automation
3. No worktree isolation for parallelization

### Recommended Investments
1. Create adws/adw_modules/agent.py
2. Add gateway script (adw_prompt.py)
3. Create composed workflow for common tasks

### Time Investment Analysis
- Current: ~20% agentic layer
- Target: 50%+ agentic layer
- Gap: Need 30% more investment in agentic work

Anti-Patterns to Identify

  • Commands exist but no specs (templates unused)
  • Specs exist but no ADWs (manual execution)
  • Many one-off scripts instead of composed workflows
  • Application layer dominant (>70% of codebase)

Version History

  • v1.0.0 (2025-12-26): Initial release

Last Updated

Date: 2025-12-26 Model: claude-opus-4-5-20251101

Didn't find tool you were looking for?

Be as detailed as possible for better results